mirror of
https://github.com/lordmathis/CUDANet.git
synced 2025-11-06 01:34:22 +00:00
100 lines
2.8 KiB
Plaintext
100 lines
2.8 KiB
Plaintext
#include <cuda_runtime_api.h>
|
|
#include <gtest/gtest.h>
|
|
|
|
#include <iostream>
|
|
|
|
#include "activation_functions.cuh"
|
|
|
|
TEST(ActivationFunctionsTest, SigmoidSanityCheck) {
|
|
cudaError_t cudaStatus;
|
|
|
|
float input[3] = {-100.0f, 0.0f, 100.0f};
|
|
|
|
std::vector<float> expected_output = {0.0f, 0.5f, 1.0f};
|
|
|
|
float* d_input;
|
|
float* d_output;
|
|
|
|
cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * 3);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * 3);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
cudaStatus =
|
|
cudaMemcpy(d_input, input, sizeof(float) * 3, cudaMemcpyHostToDevice);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
CUDANet::Kernels::sigmoid<<<1, 3>>>(d_input, d_output, 3);
|
|
cudaStatus = cudaDeviceSynchronize();
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
std::vector<float> output(3);
|
|
|
|
cudaStatus = cudaMemcpy(
|
|
output.data(), d_output, sizeof(float) * 3, cudaMemcpyDeviceToHost
|
|
);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
EXPECT_NEAR(expected_output[i], output[i], 1e-5);
|
|
}
|
|
|
|
cudaFree(d_input);
|
|
cudaFree(d_output);
|
|
}
|
|
|
|
TEST(ActivationFunctionsTest, SoftmaxExpTest) {
|
|
cudaError_t cudaStatus;
|
|
|
|
float input[6] = {22.496f, 36.9006f, 30.9904f,
|
|
28.4213f, 26.4541f, 31.7887f};
|
|
|
|
std::vector<float> expected = {5886928896.0f, 1.06102872080384e+16f,
|
|
28771323215872.0f, 2204012904448.0f,
|
|
308226162688.0f, 63922983927808.0f};
|
|
|
|
float* d_input;
|
|
float* d_output;
|
|
|
|
cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * 6);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * 6);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
cudaStatus =
|
|
cudaMemcpy(d_input, input, sizeof(float) * 6, cudaMemcpyHostToDevice);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
CUDANet::Kernels::softmax_exp<<<1, 6>>>(d_input, d_output, 6);
|
|
cudaStatus = cudaDeviceSynchronize();
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
std::vector<float> output(6);
|
|
|
|
cudaStatus = cudaMemcpy(
|
|
output.data(), d_output, sizeof(float) * 6, cudaMemcpyDeviceToHost
|
|
);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
|
|
for (int i = 0; i < 6; i++) {
|
|
EXPECT_NEAR(expected[i], output[i], 1e7);
|
|
}
|
|
|
|
cudaFree(d_input);
|
|
cudaFree(d_output);
|
|
}
|
|
|
|
TEST(ActivationFunctionsTest, SoftmaxSumTest) {
|
|
cudaError_t cudaStatus;
|
|
|
|
std::vector<float> input = {5886928896.0f, 1.06102872080384e+16f,
|
|
28771323215872.0f, 2204012904448.0f,
|
|
308226162688.0f, 63922983927808.0f};
|
|
|
|
float* d_input;
|
|
|
|
cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * 6);
|
|
EXPECT_EQ(cudaStatus, cudaSuccess);
|
|
} |